New data structures for orthogonal range queries
SIAM Journal on Computing
Regular Article: Generalized Sequence Alignment and Duality
Advances in Applied Mathematics
A polyhedral approach to sequence alignment problems
Discrete Applied Mathematics - Special volume on combinatorial molecular biology
Segment-Based Scores for Pairwise and Multiple Sequence Alignments
ISMB '98 Proceedings of the 6th International Conference on Intelligent Systems for Molecular Biology
Heaviest Increasing/Common Subsequence Problems
CPM '92 Proceedings of the Third Annual Symposium on Combinatorial Pattern Matching
The Maximum Weight Trace Problem in Multiple Sequence Alignment
CPM '93 Proceedings of the 4th Annual Symposium on Combinatorial Pattern Matching
A data structure for orthogonal range queries
SFCS '78 Proceedings of the 19th Annual Symposium on Foundations of Computer Science
BpMatch: An Efficient Algorithm for a Segmental Analysis of Genomic Sequences
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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Comparison of large, unfinished genomic sequences requires fast methods that are robust to misordering, misorientation, and duplications. A number of fast methods exist that can compute local similarities between such sequences, from which an optimal one-to-one correspondence might be desired. However, existing methods for computing such a correspondence are either too costly to run or are inappropriate for unfinished sequence. We propose an efficient method for refining a set of segment matches such that the resulting segments are of maximal size without non-identity overlaps. This resolved set of segments can be used in various ways to compute a similarity measure between any two large sequences, and hence can be used in alignment, matching, or tree construction algorithms for two or more sequences.